Project abstract Several attempts have been made to identify the genes associated with risk of alcoholism and related traits. Genes thus far implicated via linkage, candidate gene and GWAS account for only a small fraction of the overall risk, with effects varying across populations. Even the polygenic risk scores generated using all of the significant loci in the many large discovery datasets are unable to predict the disease outcome in the replication datasets. This suggests that much of the missing heritability for substance dependence and other complex disorders may be attributed to heterogeneity in phenotype definition, contribution of rare variants, gene x environment interplay and epigenetic modifications in the tissues of interest. There is some evidence in the plant and animal literature that show that the epigenetic signatures can also be passed down the generations. There is also ample evidence that show that the selective silencing of parent specific genes (genomic imprinting) can cause ?hemizygous? expression of genes. Now if the causal variants are on the background of silenced (imprinted) genes, they will never express and carrier individual will exhibit normal phenotype. This person with normal phenotype will considered as control and association analysis will not be able to identify this causal variant. In this proposal we intend to perform one of the largest meta-analysis of parent of origin analysis to identify the imprinted regions in the genome. We will further overlay the identified imprinted genomic regions on the genes showing mono-allelic mRNA expression in the RNASeq experiments on post-mortem brain samples from controls and alcohol dependent subjects. The regions with significant evidence of imprinting will be further followed in the extended high-risk addiction families using the appropriate high-throughput genomic methods to identify epigenetic signatures. This will help us to validate the imprinted regions and identify the trans-generational epigenomic effects in the addicts. The hypothesis proposed in the current proposal has never been explored at the genome-wide level in the complex disorders. The success of this work will provide the ample evidence for the trans-generational epigenetics as well as it will help us to identify many hidden causal variants and genes never identified by the regular genome-wide association studies. These genes will surely help us to identify the novel pathways and targets for the drug discovery. Last but not least this proposal will generate a vast amount of epigenetic and RNASeq data. The data will be made available on the dbGAP as a resource to be used by other researchers.